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Rapsys Technologies Pte Ltd.

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Data Engineer with kafka

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Summary

On-site Data Engineer in Singapore who designs and maintains batch and real-time data pipelines (Kafka), builds ETL/integration processes, ensures data quality, and develops dashboards and reports. Requires strong Python/SQL skills and experience with cloud data platforms.

We're Hiring: Data Engineer with Kafka!

We are looking for a skilled Data Engineer with expertise in Kafka to join our dynamic team. The ideal candidate will have at least 4 years of experience in data engineering, strong knowledge of real-time data streaming, and a passion for building robust data pipelines that empower business decisions.

Location: Singapore, Singapore

Work Mode: Work from Office

Role: Data Engineer with Kafka

Key Responsibilities (Job Requirements)

  • 1 Data Engineering & Platform Support
  • 2 Design and maintain basic data pipelines and integration processes to support reliable data flow and ensure data availability for analytics.
  • 3 Implement and monitor data validation and cleansing routines to improve data quality and ensure accurate reporting.
  • 4 Support and troubleshoot operational issues in data pipelines and databases to maintain smooth and continuous platform performance.
  • 5 Develop and update dashboards and reports to visualize key metrics and support data-driven decision-making across teams.
  • 1 Collaboration & Business Understanding
  • 2 Collaborate with stakeholders to gather data requirements and ensure solutions align with business needs and objectives.
  • 3 Communicate data insights and findings in a clear and actionable manner to support informed decision-making by non-technical stakeholders.
  • 4 Assist in analyzing structured and unstructured data to identify trends and patterns that contribute to solving business problems.
  • 1 Learning & Continuous Improvement
  • 2 Research and apply suitable machine learning models or statistical techniques under guidance to support business use cases.
  • Stay updated on industry trends and tools in data engineering and analytics to enhance technical skills and contribute to team innovation.
  • - Recommend and support process improvements to increase data pipeline efficiency and improve data reliability over time.

Job Requirements / Job Qualifications

  • Bachelor's degree in Computer Science, Data Science, Statistics, or a related field.
  • At least 8 years' working experience in data platform, data analytics or relevant projects.
  • Proven experience as a Data Engineer, with design and managing enterprise data architecture, including batch and real time processing.
  • Solid programming skills in languages such as Python, SQL, SAS, or R for data analysis and data engineering tasks.
  • Prior experience as a Data Engineer, with a demonstrated ability to design and implement data models, ETL processes, and data integration solutions.
  • Proven experience in at least one major data processing tool (Informatica, Kettle, Talend, Airflow, Dolphin etc.).
  • Prior experience with cloud-based data platforms (e.g., Azure Data Factory, Azure Purview, Databricks, Snowflake, Kafka, or equivalent) and data storage technologies (e.g., SQL/NoSQL, Vector and Graph etc.).
  • Excellent problem-solving skills and the ability to work with large, complex data sets.
  • Strong attention to detail, ensuring data accuracy and reliability in all analyses.
  • Effective communication skills to convey complex technical concepts to non-technical stakeholders.
  • Proven ability to work independently as well as collaboratively in a fast-paced, team-oriented environment.
  • Prior experience of AI technology stack is a great plus.
  • Prior experience in at least one BI tool (Power BI, Tableau, etc.).
  • Related industry experience is a plus.

Core Competency

  • Data Analytics
  • Design thinking
  • Business Needs Analysis
  • Data Engineering
  • Data Quality Assurance
  • Data Security & Compliance

Skills

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See also

Data Engineering jobs by country — openings, pay and top skills →

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